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<\/p>\nToday\u2019s explosion of AI service providers has everyone looking back at the dot-com bubble, revisiting the technological boom and bust at the turn of the millennia for historical precedent to help us separate real innovation from BS.\u00a0<\/p>\n
History is a valuable teacher, but I look beyond the history of the ad tech industry for inspiration. Case in point: the shipping container revolution. It teaches us that the most revolutionary changes to a business are often grounded in making day-to-day processes more straightforward and interoperable.<\/p>\n
Bear with me for a moment. Prior to the 1950s, ocean freight was slow, unpredictable, expensive, utilized extensive manual labor and had high rates of damage and theft. By the 1960s, however, global supply chains had become streamlined and predictable, all while making shipping faster, more secure and vastly less expensive. Was this advancement enabled by a breakthrough in shipbuilding technology? Nope. Ships changed dramatically after the 1950s, but their evolution was spurred by an earlier innovation: the intermodal container.<\/p>\n
In the early 1950s, Malcom McLean invented today\u2019s ubiquitous shipping container: a standardized steel crate that could move seamlessly between ships, trucks and trains without ever being opened. Loading that once took days now took hours, enabling the globalization that is the bedrock of today\u2019s supply chains. Malcom McLean\u2019s impact was due to his ability to understand the challenges faced by the shipping industry and apply innovation through an interoperable system that worked with existing carriers, ports and manufacturers. <\/p>\n
<\/p>\n
To return to the marketing discipline, there is an industry myth that end-to-end platforms and sheer quantity of data yield efficiency and competitive advantage. But most clients need flexible, modular solutions that address their business needs and work with their existing tech stacks.\u00a0<\/p>\n
A modular approach to marketing<\/p>\n
Our role as agency partners is not to redesign our clients\u2019 \u201cships\u201d but to create solutions that allow them to deploy their cargo more efficiently and effectively.\u00a0<\/p>\n
I call this a \u201cblack book\u201d approach rather than a \u201cblack box.\u201d Where a black box is an agency-owned, one-size-fits-all solution, a black book is modular by design and client-owned by intent, operating with transparency and flexibility. It\u2019s a system for assembling the right data, tools and workflows with implications across three critical layers for marketers: data, technology and agents.\u00a0\u00a0\u00a0<\/p>\n
When it comes to data, a black book approach means thinking in terms of context rather than quantity.\u00a0<\/p>\n
Relevance, freshness, rights, cost and geographic validity matter for more than sheer scale. Marketers should interrogate whether the data their agency delivers truly outperforms their existing baseline. A black book mentality seeks to orchestrate the right data for clients, not to meet a platform payback requirement. Rather than an inflexible black box, in this purpose-built approach, the logic is visible, interrogable and adaptable to each client\u2019s needs and systems.<\/p>\n
To go back to the shipping analogy: For brands, AI should plug leaks and gaps in their ship, not require a rebuild.\u00a0<\/p>\n
Clients are often surprised when I tell them that their tech stack should matter more than their agency\u2019s. I think this is the result of too many agency-client relationships that try to force long-term technology dependence. But brands shouldn\u2019t reorient themselves around their agencies\u2019 AI tech. Not only is that a bad practice, it\u2019s an ineffective one; needs vary across organizations of different geographies, verticals and maturity, and they change over time.\u00a0<\/p>\n
A black book strategy means that clients can adapt what they need rather than an all-or-nothing approach to tech. They can take their data, institutional knowledge and IP with them even after the agency-client relationship ends.<\/p>\n
Putting AI in practitioners\u2019 hands<\/p>\n
Malcom McLean was not an engineer; he was a trucker. He was able to revolutionize the shipping industry because he had an intimate understanding of its problems. This depth of human insight has never been more relevant than with the development of agentic AI.\u00a0<\/p>\n
Just like Malcom McLean, the media practitioners who are closest to the problem often design the best solutions. The black book approach means creating low- and no-code tools that allow teams to build agents that improve their own workflows. Engineers and data scientists can then be deployed to industrialize what works rather than rolling out agents that create more noise than true business impact.<\/p>\n
Today, marketers face immense pressure to integrate AI into all facets of their organization. New platforms and partners are seemingly announced every day, efficiency claims are made with little validation to back them up and investors crown winners and punish perceived laggards well ahead of actual commercial outcomes.\u00a0<\/p>\n
However, amid this landscape that is saturated with noise, it\u2019s important to remember that the future doesn\u2019t belong to who can tell their story the loudest. It belongs to those who understand business problems and create innovations that work in the real world, not just in the boardroom.\u00a0<\/p>\n
The solutions that generate ROI don\u2019t always go viral online and earn impressions on social feeds. Sometimes it\u2019s a simple, unassuming metal container that changes the world.\u00a0\u00a0<\/p>\n
\u201cData-Driven Thinking<\/a>\u201d is written by members of the media community and contains fresh ideas on the digital revolution in media.<\/p>\n Follow Havas<\/a>, Dan Hagen<\/a> and AdExchanger<\/a> on LinkedIn.<\/p>\n","protected":false},"excerpt":{"rendered":"Today\u2019s explosion of AI service providers has everyone looking back at the dot-com bubble, revisiting the technological boom…\n","protected":false},"author":2,"featured_media":46418,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[28033,28032,179,7493,28034,28035,1085,14777,28036,8024,28037],"class_list":["post-46417","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agentic-ai","tag-ad-agency-holding-companies","tag-ad-tech-containerization","tag-agentic-ai","tag-agentic-artificial-intelligence","tag-containerization","tag-dan-hagen","tag-data-science","tag-data-driven-thinking","tag-havas","tag-interoperability","tag-malcom-mclean"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/46417","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=46417"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/46417\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/46418"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=46417"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=46417"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=46417"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}